MétaCan
Menu
Back to cohort

Protein content in milk of holstein black-and-white cows

2020· article· en· W3109632059 on OpenAlexaboutno aff
N. L. Ignatieva, E Yu Nemtseva

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsBreedCaseinBiologyTransaminationAnimal scienceMilk proteinFood scienceAmino acidBiochemistry

Abstract

fetched live from OpenAlex

Abstract The most optimal method to solve the problem for cow’s milk and protein content increase is to carry out zootechnical and breeding activities. The goal was to study the milk protein structure and content of the Holsteinized black-and-white breed cows of different genotypes, as well as to establish the relationship nature between the activity of transamination enzymes and the milk protein content of cows. For this purpose, 4 groups of experimental cows (15 heads in each) were formed according to the principle of father’s belonging to the countries of origin (daughters of seed bulls of Canadian, Danish selection, Dutch and domestic selection). The superiority of cows-daughters of foreign breeding bulls in terms of milk protein content was established. Moreover, the milk of cows born from foreign producers contents high level of casein - the most important fraction from the technological point of view. Electrophoretic analysis of milk proteins isolated 16 fractions, including 9 casein and 7 whey ones. The highest content was found in such fractions as αs1-, β-, αs2-, κ-caseins and β-Lg. The calculated correlation coefficients between the alanine aminotransferase and aspartate aminotransferase and the milk protein activity of cows showed a direct relationship between them in cows of the studied groups. This is a favorable factor for increasing the cows milk protein content.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.618

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.192
Teacher spread0.147 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations9
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicFood Industry and Aquatic BiologyFrench-language works237,207